An update on the formation in tobacco, toxicity and carcinogenicity of N'-nitrosonornicotine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone.

The tobacco-specific nitrosamines N'-nitrosonornicotine (NNN) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) are considered 'carcinogenic to humans' by the International Agency for Research on Cancer (IARC) and are believed to be important in the carcinogenic effects of both smokeless tobacco and combusted tobacco products. This short review focuses on the results of recent studies on the formation of NNN and NNK in tobacco, and their carcinogenicity and toxicity in laboratory animals. New mechanistic insights are presented regarding the role of dissimilatory nitrate reductases in certain microorganisms involved in the conversion of nitrate to nitrite that leads to the formation of NNN and NNK during curing and processing of tobacco. Carcinogenicity studies of the enantiomers of the major NNK metabolite 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and the enantiomers of NNN are reviewed. Recent toxicity studies of inhaled NNK and co-administration studies of NNK with formaldehyde, acetaldehyde, acrolein and CO2, all of which occur in high concentrations in cigarette smoke, are discussed.

Safety Assessment of Capryloyl Salicylic Acid as Used in Cosmetics.

The Expert Panel for Cosmetic Ingredient Safety (Panel) reassessed the safety of Capryloyl Salicylic Acid in cosmetic products; this ingredient is reported to function as a skin conditioning agent. The Panel reviewed relevant data relating to the safety of this ingredient in cosmetic formulations, and concluded that the available data are insufficient to make a determination that Capryloyl Salicylic Acid is safe under the intended conditions of use in cosmetic formulations.

Safety Assessment of Polysilicone-11 as Used in Cosmetics.

The Expert Panel for Cosmetic Ingredient Safety (Panel) assessed the safety of Polysilicone-11 as used in cosmetic formulations. This ingredient is reported to function as a film former. The Panel considered the available data and concluded that Polysilicone-11 is safe in cosmetics in the present practices of use and concentration described in this safety assessment.

Safety Assessment of Palm-Derived Ingredients as Used in Cosmetics.

The Expert Panel for Cosmetic Ingredient Safety (Panel) reviewed the safety of 8 palm tree (Euterpe edulis (juçara) and Euterpe oleracea (açaí))-derived ingredients as used in cosmetic products; these ingredients are reported to function mostly as skin conditioning agents. The Panel reviewed relevant data relating to the safety of these ingredients in cosmetic formulations. Industry should continue to use good manufacturing practices to limit impurities. The Panel concluded that palm tree (açaí and juçara)-derived ingredients are safe in cosmetics in the present practices of use and concentration described in this safety assessment.

Safety Assessment of Soy-Derived Ingredients as Used in Cosmetics.

The Expert Panel for Cosmetic Ingredient Safety (Panel) reviewed the safety of 28 soy-derived ingredients as used in cosmetic products. These ingredients are reported to primarily function as antioxidants, skin protectants, skin-conditioning agents, and hair-conditioning agents. The Panel considered the available data relating to the safety of these ingredients in cosmetic formulations, and concluded that 24 of the 28 soy-derived ingredients are safe in cosmetics in the present practices of use and concentration described in this safety assessment. The Panel also concluded that the available data are insufficient to make a determination that Glycine Max (Soybean) Callus Culture, Glycine Max (Soybean) Callus Culture Extract, Glycine Max (Soybean) Callus Extract, and Glycine Max (Soybean) Phytoplacenta Conditioned Media are safe under the intended conditions of use in cosmetic formulations.

Preoperative prediction model for risk of readmission after total joint replacement surgery: a random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness.

BACKGROUND: The Center for Medicare and Medicaid Services (CMS) imposes payment penalties for readmissions following total joint replacement surgeries. This study focuses on total hip, knee, and shoulder arthroplasty procedures as they account for most joint replacement surgeries. Apart from being a burden to healthcare systems, readmissions are also troublesome for patients. There are several studies which only utilized structured data from Electronic Health Records (EHR) without considering any gender and payor bias adjustments. METHODS: For this study, dataset of 38,581 total knee, hip, and shoulder replacement surgeries performed from 2015 to 2021 at Novant Health was gathered. This data was used to train a random forest machine learning model to predict the combined endpoint of emergency department (ED) visit or unplanned readmissions within 30 days of discharge or discharge to Skilled Nursing Facility (SNF) following the surgery. 98 features of laboratory results, diagnoses, vitals, medications, and utilization history were extracted. A natural language processing (NLP) model finetuned from Clinical BERT was used to generate an NLP risk score feature for each patient based on their clinical notes. To address societal biases, a feature bias analysis was performed in conjunction with propensity score matching. A threshold optimization algorithm from the Fairlearn toolkit was used to mitigate gender and payor biases to promote fairness in predictions. RESULTS: The model achieved an Area Under the Receiver Operating characteristic Curve (AUROC) of 0.738 (95% confidence interval, 0.724 to 0.754) and an Area Under the Precision-Recall Curve (AUPRC) of 0.406 (95% confidence interval, 0.384 to 0.433). Considering an outcome prevalence of 16%, these metrics indicate the model's ability to accurately discriminate between readmission and non-readmission cases within the context of total arthroplasty surgeries while adjusting patient scores in the model to mitigate bias based on patient gender and payor. CONCLUSION: This work culminated in a model that identifies the most predictive and protective features associated with the combined endpoint. This model serves as a tool to empower healthcare providers to proactively intervene based on these influential factors without introducing bias towards protected patient classes, effectively mitigating the risk of negative outcomes and ultimately improving quality of care regardless of socioeconomic factors.

Association of diet with per- and polyfluoroalkyl substances in plasma and human milk in the New Hampshire Birth Cohort Study.

Per- and polyfluoroalkyl substances (PFAS) are related to various adverse health outcomes, and food is a common source of PFAS exposure. Dietary sources of PFAS have not been adequately explored among U.S. pregnant individuals. We examined associations of dietary factors during pregnancy with PFAS concentrations in maternal plasma and human milk in the New Hampshire Birth Cohort Study. PFAS concentrations, including perfluorohexane sulfonate (PFHxS), perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), perfluorononanoate (PFNA), and perfluorodecanoate (PFDA), were measured in maternal plasma collected at ∼28 gestational weeks and human milk collected at ∼6 postpartum weeks. Sociodemographic, lifestyle and reproductive factors were collected from prenatal questionnaires and diet from food frequency questionnaires at ∼28 gestational weeks. We used adaptive elastic net (AENET) to identify important dietary variables for PFAS concentrations. We used multivariable linear regression to assess associations of dietary variables selected by AENET models with PFAS concentrations. Models were adjusted for sociodemographic, lifestyle, and reproductive factors, as well as gestational week of blood sample collection (plasma PFAS), postpartum week of milk sample collection (milk PFAS), and enrollment year. A higher intake of fish/seafood, eggs, coffee, or white rice during pregnancy was associated with higher plasma or milk PFAS concentrations. For example, every 1 standard deviation (SD) servings/day increase in egg intake during pregnancy was associated with 4.4 % (95 % CI: 0.6, 8.4), 3.3 % (0.1, 6.7), and 10.3 % (5.6, 15.2) higher plasma PFOS, PFOA, and PFDA concentrations respectively. Similarly, every 1 SD servings/day increase in white rice intake during pregnancy was associated with 7.5 % (95 % CI: -0.2, 15.8) and 12.4 % (4.8, 20.5) greater milk PFOS and PFOA concentrations, respectively. Our study suggests that certain dietary factors during pregnancy may contribute to higher PFAS concentrations in maternal plasma and human milk, which could inform interventions to reduce PFAS exposure for both birthing people and offspring.

Human cancer genomes harbor the mutational signature of tobacco-specific nitrosamines NNN and NNK.

Tobacco usage is linked to multiple cancer types and accounts for a quarter of all cancer-related deaths. Tobacco smoke contains various carcinogenic compounds, including polycyclic aromatic hydrocarbons (PAH), though the mutagenic potential of many tobacco-related chemicals remains largely unexplored. In particular, the highly carcinogenic tobacco-specific nitrosamines NNN and NNK form pre-mutagenic pyridyloxobutyl (POB) DNA adducts. In the study presented here, we identified genome-scale POB-induced mutational signatures in cell lines and rat tumors, while also investigating their role in human cancer. These signatures are characterized by T>N and C>T mutations forming from specific POB adducts damaging dT and dC residues. Analysis of 2,780 cancer genomes uncovered POB signatures in ∼180 tumors; from cancer types distinct from the ones linked to smoking-related signatures SBS4 and SBS92. This suggests that, unlike PAH compounds, the POB pathway may contribute uniquely to the mutational landscapes of certain hematological malignancies and cancers of the kidney, breast, prostate and pancreas.